Machine Vision Based Techniques for Automatic Mango Fruit Sorting and Grading Based on Maturity Level and Size

Technology which will be develoved on this study is aimed to detect the maturity of the optimum mango to reduce the risk of mangoes that decay before the distribution is by utilizing LDR-based color sensor technology (Light Dependent Resistor). Where the principle works that is when given light on the surface of the skin of mango fruit then the light will be reproduced captured by the sensor and pass through the filter then if the same color then the filter will absorb the light. The results obtained that mango detected maturity level using LDR more efficient and accurate where mango has optimum maturity level has an output voltage interval of 150.68 mV - 155.45 mV. Where this technology is expected to increase mango productivity in Indonesia so as to increase exports to other countries that can support the world of agriculture.

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Mango Fruit Inspection Technique through Machine Vision System

i-manager’s Journal on Future Engineering and Technology ◽

10.26634/jfet.11.1.3657 ◽

2015 ◽

Vol 11 (1) ◽

pp. 32-36

Author(s):

Abarna J ◽

◽

Arockia Selvakumar A. ◽

Keyword(s):

Machine Vision ◽

Vision System ◽

Machine Vision System ◽

Mango Fruit

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Machine Vision

10.1017/cbo9781139168229 ◽

2009 ◽

Cited By ~ 15

Author(s):

Wesley E. Snyder ◽

Hairong Qi

Keyword(s):

Machine Vision

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Classroom Lighting Energy-Saving Control System Based on Machine Vision Technology

Light & Engineering ◽

10.33383/2018-135 ◽

2018 ◽

pp. 143-149 ◽

Cited By ~ 1

Author(s):

Ruijie CHENG

Keyword(s):

Control System ◽

Machine Vision ◽

Energy Saving ◽

Back Propagation ◽

Back Propagation Neural Network ◽

Lighting Control ◽

Lighting Energy ◽

Neural Network Algorithm ◽

Energy Saving Control ◽

Model Algorithm

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multifeedback model for energysaving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.

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